Instructions to use Gwen01/ProctorVision-Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Gwen01/ProctorVision-Models with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://Gwen01/ProctorVision-Models") - Notebooks
- Google Colab
- Kaggle
Download best_cheat_mnv2.keras from Gwen01/ProctorVision-Models: direct link, hf CLI and curl.
- Browser
- Download file 26.2 MB
-
https://huggingface.co/Gwen01/ProctorVision-Models/resolve/main/best_cheat_mnv2.keras
- Command line
-
hf download hf://Gwen01/ProctorVision-Models/best_cheat_mnv2.keras
-
curl -L -o best_cheat_mnv2.keras https://huggingface.co/Gwen01/ProctorVision-Models/resolve/main/best_cheat_mnv2.keras
26.2 MB
- Xet hash:
- bc3a049661bd193f71fe754d78324902949c03226a8b0e8ff404b9e62abaf04b
- Size of remote file:
- 26.2 MB
- SHA256:
- 4c110834c2ef052d41b19a20f30fa2b9d4145b8aba5bebf86661d5c3b21ba09e
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